Interneuron Loss and Microglia Activation by Transcriptome Analyses in the Basal Ganglia of Tourette Disorder.

Background: Tourette disorder (TS) is characterized by motor hyperactivity and tics that are believed to originate in the basal ganglia. Postmortem immunocytochemical analyses has revealed decreases in cholinergic (CH), as well as parvalbumin and somatostatin GABA (gamma-aminobutyric acid) interneurons (INs) within the caudate/putamen of individuals with TS.

Methods: We obtained transcriptome and open chromatin datasets by single-nucleus RNA sequencing and single-nucleus ATAC sequencing, respectively, from caudate/putamen postmortem specimens of 6 adults with TS and 6 matched normal control subjects.

Genome-wide analysis and visualization of copy number with CNVpytor in igv.js.

Summary: Copy number variation (CNV) and alteration (CNA) analysis is a crucial component in many genomic studies and its applications span from basic research to clinic diagnostics and personalized medicine. CNVpytor is a tool featuring a read depth-based caller and combined read depth and B-allele frequency (BAF) based 2D caller to find CNVs and CNAs. The tool stores processed intermediate data and CNV/CNA calls in a compact HDF5 file-pytor file.

Correction: All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons.

[This corrects the article DOI: 10.1371/journal.pcbi.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions.

All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons.

Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing a cell's genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell without the need for data from bulk(s).

CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing.

Background: Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole-genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth.

Findings: Herein, we present an extension of CNVnator developed in Python-CNVpytor.

H Nuclear Magnetic Resonance Spectroscopy-Based Methods for the Quantification of Proteins in Urine.

We described several postprocessing methods to measure protein concentrations in human urine from existing H nuclear magnetic resonance (NMR) metabolomic spectra: (1) direct spectral integration, (2) integration of NCD spectra (NCD = 1D NOESY-CPMG), (3) integration of SMolESY-filtered 1D NOESY spectra (SMolESY = Small Molecule Enhancement SpectroscopY), (4) matching protein patterns, and (5) TSP line integral and TSP linewidth. Postprocessing consists of (a) removal of the metabolite signals (demetabolization) and (b) extraction of the protein integral from the demetabolized spectra. For demetabolization, we tested subtraction of the spin-echo 1D spectrum (CPMG) from the regular 1D spectrum and low-pass filtering of 1D NOESY by its derivatives (c-SMolESY).

Magnetisation Processes in Geometrically Frustrated Spin Networks with Self-Assembled Cliques.

Functional designs of nanostructured materials seek to exploit the potential of complex morphologies and disorder. In this context, the spin dynamics in disordered antiferromagnetic materials present a significant challenge due to induced geometric frustration. Here we analyse the processes of magnetisation reversal driven by an external field in generalised spin networks with higher-order connectivity and antiferromagnetic defects.

Large-scale influence of defect bonds in geometrically constrained self-assembly.

Recently, the importance of higher-order interactions in the physics of quantum systems and nanoparticle assemblies has prompted the exploration of new classes of networks that grow through geometrically constrained simplex aggregation. Based on the model of chemically tunable self-assembly of simplexes [Šuvakov et al., Sci.

Hidden geometries in networks arising from cooperative self-assembly.

Multilevel self-assembly involving small structured groups of nano-particles provides new routes to development of functional materials with a sophisticated architecture. Apart from the inter-particle forces, the geometrical shapes and compatibility of the building blocks are decisive factors. Therefore, a comprehensive understanding of these processes is essential for the design of assemblies of desired properties.

Gravitational waves from periodic three-body systems.

Three bodies moving in a periodic orbit under the influence of Newtonian gravity ought to emit gravitational waves. We have calculated the gravitational radiation quadrupolar waveforms and the corresponding luminosities for the 13+11 recently discovered three-body periodic orbits in Newtonian gravity. These waves clearly allow one to distinguish between their sources: all 13+11 orbits have different waveforms and their luminosities (evaluated at the same orbit energy and body mass) vary by up to 13 orders of magnitude in the mean, and up to 20 orders of magnitude for the peak values.

Three classes of newtonian three-body planar periodic orbits.

We present the results of a numerical search for periodic orbits of three equal masses moving in a plane under the influence of Newtonian gravity, with zero angular momentum. A topological method is used to classify periodic three-body orbits into families, which fall into four classes, with all three previously known families belonging to one class. The classes are defined by the orbits' geometric and algebraic symmetries.

How the online social networks are used: dialogues-based structure of MySpace.

Quantitative study of collective dynamics in online social networks is a new challenge based on the abundance of empirical data. Conclusions, however, may depend on factors such as user's psychology profiles and their reasons to use the online contacts. In this study, we have compiled and analysed two datasets from MySpace.

Approximate action-angle variables for the figure-eight and periodic three-body orbits.

We use the maximally permutation-symmetric set of three-body coordinates that consist of the "hyper-radius" R=√[ρ(2)+λ(2)], the "rescaled area of the triangle" √[3]/2R(2) |ρ×λ|), and the (braiding) hyperangle Φ=arctan(2ρ·λ/λ(2)-ρ(2)) to analyze the "figure-eight" choreographic three-body motion discovered by Moore [Phys. Rev. Lett.

Modeling collective charge transport in nanoparticle assemblies.

Mapping the assembled patterns of nanoparticles onto networks (mathematical graphs) provides a way for quantitative analysis of the structure effects on the physical properties of the assembly. Here we review the network modeling of the conduction with single-electron tunneling mechanisms in the assembled nanoparticle films. Simulations of the conduction predict the nonlinear current-voltage curves in different classes of the nanoparticle networks.

Efficient hidden-variable simulation of measurements in quantum experiments.

We prove that the results of a finite set of general quantum measurements on an arbitrary dimensional quantum system can be simulated using a polynomial (in measurements) number of hidden-variable states. In the limit of infinitely many measurements, our method gives models with the minimal number of hidden-variable states, which scales linearly with the number of measurements. These results can find applications in foundations of quantum theory, complexity studies, and classical simulations of quantum systems.

Charge transport in cellular nanoparticle networks: meandering through nanoscale mazes.

The transport of electrons through topologically complex two-dimensional Au nanoparticle networks has been investigated using a combination of low temperature (4.5 K) direct current I(V) measurements and numerical simulations. Intricate, spatially correlated nanostructured networks were formed via spin-casting.